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opencc-by-4.0Apr 2024View details →

Data for "Seed production in a dioecious subcanopy conifer tree Taxus baccata: the positive effect of neighboring males and female heterozygosity"

A spreadsheet contains data for individual trees of Taxus baccata collected within the "Wadernik" reserve, Poland. Data include spatial coordinates (in meters), altitude (in meters), trunk perimeter (in centimeters), canopy closure assessment (0-fully open, 10-complete closure), the observed seed number, sex expression (female/male/undetermined), and genotypes at 20 microsatellite markers.

opencc-zeroMar 2022View details →

VCF files of common grassland plants from wild collected seeds of 19 common European grassland species with up to 4 consecutive generations grown in monoculture for seed production for restoration

A growing number of restoration projects require large amounts of seeds. As harvesting natural populations cannot cover the demand, wild plants are often propagated in large-scale monocultures. There are concerns that this cultivation process may cause genetic drift and unintended selection, which would alter the genetic properties of the cultivated populations and reduce their genetic diversity. Such changes could reduce the pre-existing adaptation of restored populations, and limit their adaptability to environmental change. We used single nucleotide polymorphism (SNP) markers and a pool-sequencing approach to test for genetic differentiation and changes in gene diversity during cultivation in 19 wild grassland species, comparing the source populations and up to four consecutive cultivation generations. We then linked the magnitudes of genetic changes to the species' breeding systems and seed dormancy, to understand the roles of these traits in genetic change. The propagation changed the genetic composition of the cultivated generations only moderately. The genetic differentiation we observed as a consequence of cultivation was much lower than the natural genetic differentiation between different source regions. The propagated generations harbored even higher gene diversity than wild-collected seeds. Genetic change was stronger in self-compatible than in self-incompatible species, probably as a result of increased outcrossing in the monocultures. Synthesis and applications: Our study indicates that large-scale seed production maintains the genetic integrity of natural populations. Increased genetic diversity may be indicative of increased adaptive potential of propagated seeds, which would make them especially suitable for ecological restoration. Yet, it remains to be tested whether these patterns observed on the level of molecular markers will be mirrored also in plant phenotypes. Further, we used seeds produced in Germany and Austria, where the seed production is regulated and certified. Whether other seed production systems perform equally well remains to be tested.

Figure 7 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis

Figure 7. Results from the sensitivity analysis depicting variations in the overall effect size estimates (mean ± 95% confidence intervals [CIs]) of water-stress effects on (A) weed germination/emergence, (B) seedling radicle/root length, (C) plant height, and (D) leaf area when a particular study is omitted from the analysis. The vertical black solid and dashed lines represent overall effect sizes (mean ± 95% CIs) with all studies included.

Figure 3 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis

Figure 3. Overall water-stress effects on germination/emergence of grass and broadleaf weeds (top) and six weed families—Asteraceae, Fabaceae, Convolvulaceae, Amaranthaceae, Rubiaceae, and Poaceae (bottom). The vertical black dashed line represents zero effect. The black dots are overall mean effect sizes, and the black lines are 99% confidence intervals (CIs).The values in parentheses are the number of observations followed by the number of studies for each pair-wise comparison. The mean effect sizes were considered significantly different when their 99% CIs did not include zero.

Figure 4 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis

Figure 4. The log response ratio for germination and seedling radicle length of broadleaf (green dots/line) and grass (red dots/line) weed species as a function of water-stress intensity. Water stress increased as solution osmotic potential (ψsolution) decreased and vice versa.The subgroups for germination are 0 to −0.2, −0.2 to −0.4, −0.4 to −0.6, −0.6 to −0.8, −0.8 to −1.0, −1.0 to −1.4, and <−1.4 MPa, while the subgroups for radicle length are 0 to −0.2, −0.2 to −0.4, −0.4 to −0.6, −0.6 to −1.0, and <−1.0 MPa. Only ψsolution-based studies were used in this analysis. For each subgroup, the solid dots and lines represent mean effect sizes and their corresponding 99% confidence intervals (CIs).The mean effect sizes were considered significantly different when their 99% CIs did not include zero. Similarly, the water-stress effects were significantly different for each subgroup and among weed types only when their 99% CIs did not overlap with one another. The fitted lines represent a four-parameter logistic regression model, and the coefficients of the models are presented in Table 2.

Figure 1 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis

Figure 1. PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses; Page and McKenzie 2021) flow diagram highlighting the selection procedure of 86 scientific published papers included in the meta-analysis.

Figure 8 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis

Figure 8. Results from the sensitivity analysis depicting variations in the overall effect size estimates (mean ± 95% confidence intervals [CIs]) of water-stress effects on (A) branches/tillers per plant, (B) leaves per plant, (C) inflorescences per plant, (D) seeds per plant, (E) total biomass, (F) root biomass, (G) shoot biomass, and (H) root:shoot ratio, when a particular study is omitted from the analysis. The vertical black solid and dashed lines represent overall effect sizes (mean ± 95% CIs) with all studies included.

Figure 6 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis

Figure 6. Density plots depicting the distribution of the individual effect sizes for all 12 response variables considered in this meta-analysis: (A) weed seed germination/emergence; (B) radicle/root length, plant height, and leaf area; (C) branches/tillers per plant, leaves per plant, inflorescences per plant, and seeds per plant; and (D) total biomass, root biomass, shoot biomass, and root:shoot ratio.

Figure 2 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis

Figure 2. Overall water-stress effects on weed germination/emergence, growth characteristics, and seed production. The vertical black dashed line represents zero effect. The black dots are overall mean effect sizes, and the black lines are 95% confidence intervals (CIs). The values in parentheses are the number of observations followed by the number of studies for each pair-wise comparison. The mean effect sizes were considered significantly different when their 95% CIs did not include zero.

Figure 5 in Effect of water stress on weed germination, growth characteristics, and seed production: a global meta-analysis

Figure 5. The log response ratio for weed growth characteristics (plant height, leaf area, branches/tillers per plant, leaves per plant,root biomass, shoot biomass, and root:shoot ratio) and seed production (inflorescences per plant and seeds per plant) as a function of water-stress intensity. Water stress increased as soil moisture (% field capacity) decreased and vice versa. The green and red dots represent broadleaf and grass weed species, respectively. The solid black points and the lines represent mean effect sizes and their 99% confidence intervals (CIs) for low (>60%), moderate (30%–60%), and severe (<30% field capacity) water-stress subgroups. The mean effect sizes were considered significantly different when their 99% CIs did not include zero. Similarly, the water-stress effects were significantly different for each subgroup and among weed types only when their 99% CIs did not overlap with one another.

Figure 3 in Rattail fescue (VulpiO myuros) interference and seed production as affected by sowing time and crop density in winter wheat

Figure 3. Relationships between yield components and Vulpia myuros density at two sowing times and crop densities in the growing seasons of 2017–2018 (A and C) and 2018– 2019 (B and D). Number of crop ears per square meter (A and B) and 1,000-kernel weight (C and D) data are shown with fitted curves. Data from the growing seasons of 2017–2018 and 2018–2019 were fit to the linear regression (Equation 2) and asymptotic nonlinear regression (Equation 3) models, respectively.

Figure 4 in Rattail fescue (VulpiO myuros) interference and seed production as affected by sowing time and crop density in winter wheat

Figure 4. Relationships between the per-plant seed production and Vulpia myuros density at two crop densities solely at normal sowing time in the growing season of 2017–2018 (A) and at two sowing times and crop densities in 2018–2019 (B). Data from the growing seasons of 2017–2018 and 2018–2019 were fit to the linear regression (Equation 2) and asymptotic nonlinear regression (Equation 3) models, respectively.

Figure 2 in Rattail fescue (VulpiO myuros) interference and seed production as affected by sowing time and crop density in winter wheat

Figure 2. Relationships between crop grain yield (kg ha−1) and Vulpia myuros density at two sowing times and crop densities in winter wheat in the growing seasons of 2017–2018 (A) and 2018–2019 (B). Data were fit to the rectangular hyperbola model (Equation 1).

Figure 1 in Rattail fescue (VulpiO myuros) interference and seed production as affected by sowing time and crop density in winter wheat

Figure 1. Cumulative emergence dynamics of Vulpia myuros at normal sowing time and late sowing time in relation to thermal time (C) in 2017–2018 (A) and 2018–2019 (B). Regression equation and parameter estimates described in Table 2.

opencc-by-4.0Dec 2022View details →

Figure 2. Interaction between nitrogen x phosphorus for seeds pod-1 in Role of beneficial microbes with nitrogen and phosphorous levels on canola productivity

Figure 2. Interaction between nitrogen x phosphorus for seeds pod-1 (a), phosphorous x beneficial microbes for seeds pod-1 (b), nitrogen x beneficial microbes for grains weight (c), and nitrogen x beneficial microbes for seed yield (kg ha-1) of canola (d).

opencc-zeroNov 2022View details →

Simulated pollinator decline has similar effects on seed production of female and hermaphrodite Lobelia siphilitica, but different effects on selection on floral traits

PREMISE: Pollinator decline, by reducing seed production, is predicted to strengthen natural selection on floral traits. However, the effect of pollinator decline on gender dimorphic species (such as gynodioecious species, where plants produce female or hermaphrodite flowers) may differ between the sex morphs: if pollinator decline reduces the seed production of females more than hermaphrodites, then it should also have a larger effect on selection on floral traits in females than in hermaphrodites. RESULTS: Experimentally reducing pollination decreased seed production of both females and hermaphrodites by ~21%. Reducing pollination also strengthened selection on floral traits, but this effect was not larger in females than in hermaphrodites. Instead, reducing pollination intensified selection for taller inflorescences in hermaphrodites, but did not intensify selection on any floral trait in females. CONCLUSIONS: Our results suggest that pollinator decline will not have a larger effect on either seed production or selection on floral traits of female plants. As such, any effect of pollinator decline on seed production may be similar for gender dimorphic and monomorphic species. However, the potential for floral traits of females (and thus of gender dimorphic species) to evolve in response to pollinator decline could be limited.

publicSep 2024View details →

Data from: Co-Mast: Harmonized seed production data for woody plants across U.S. long term research sites

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